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To address the low accuracy of consumer sentiment analysis in existing product recommendation scenarios, a webpage localization and sentiment analysis recommendation model is proposed that combines an improved web search algorithm with a bidirectional long short-term memory network and an attention mechanism. An e-commerce network search system is then designed around this model. Experimental results show that the sentiment analysis recommendation model achieves an accuracy of 98.88% and an average mean squared error of 1.027, outperforming all comparison models. The average root-mean-square error is 0.476, recall is 98.92%, the F1 score is 97.78%, and the recognition accuracy for each of the four emotional tendencies exceeds 95%. In addition, the integrated system delivers an average search time of 87.6 ms, a central processing unit occupancy of 44.68%, a missed-search rate of 1.42%, and a user satisfaction of 99.34%, all superior to the comparison systems. The system offers a ready-to-deploy solution for sentiment-aware product search and provides a theoretical basis for future research in e-commerce search systems.<\/jats:p>","DOI":"10.1177\/2167647x261435867","type":"journal-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T15:38:26Z","timestamp":1775662706000},"page":"193-205","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["E-Commerce Network Search System Based on Target Webpage Positioning and Sentiment Analysis Recommendation"],"prefix":"10.1177","volume":"14","author":[{"given":"Yu-Chung","family":"Hsiao","sequence":"first","affiliation":[{"name":"Business School, Nanfang College Guangzhou, Guangzhou, China."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,4,8]]},"reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.33050\/sabda.v3i1.492"},{"issue":"2","key":"e_1_3_4_3_1","first-page":"98","article-title":"\u201cA multi-party agent for privacy preference elicitation","volume":"1","author":"Salem RB","year":"2023","unstructured":"2.Salem RB, , Aimeur E, , Hage H. \u201cA multi-party agent for privacy preference elicitation. 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